Overview

Dataset statistics

Number of variables31
Number of observations56601
Missing cells229427
Missing cells (%)13.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.6 MiB
Average record size in memory956.7 B

Variable types

DateTime1
Categorical12
Numeric8
Text7
Unsupported1
Boolean2

Alerts

username has constant value "7h7t32c2zzbfixxoo414zkhul"Constant
platform is highly imbalanced (74.5%)Imbalance
conn_country is highly imbalanced (> 99.9%)Imbalance
offline is highly imbalanced (92.5%)Imbalance
incognito_mode is highly imbalanced (> 99.9%)Imbalance
user_agent_decrypted has 56601 (100.0%) missing valuesMissing
episode_name has 56369 (99.6%) missing valuesMissing
episode_show_name has 56369 (99.6%) missing valuesMissing
spotify_episode_uri has 56369 (99.6%) missing valuesMissing
artist_skip_rate_bins has 1863 (3.3%) missing valuesMissing
user_agent_decrypted is an unsupported type, check if it needs cleaning or further analysisUnsupported
ms_played has 2116 (3.7%) zerosZeros
hour has 2338 (4.1%) zerosZeros
play_count has 9796 (17.3%) zerosZeros
album_play_count has 5125 (9.1%) zerosZeros
artist_play_count has 3037 (5.4%) zerosZeros
artist_skip_rate_so_far has 1631 (2.9%) zerosZeros
current_listening_streak has 37555 (66.4%) zerosZeros

Reproduction

Analysis started2024-05-15 11:44:06.655658
Analysis finished2024-05-15 11:44:34.905987
Duration28.25 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

ts
Date

Distinct53004
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size884.4 KiB
Minimum2022-10-14 20:19:47+00:00
Maximum2024-03-21 19:23:06+00:00
2024-05-15T13:44:35.129359image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:35.517660image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

username
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 MiB
7h7t32c2zzbfixxoo414zkhul
56601 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1415025
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7h7t32c2zzbfixxoo414zkhul
2nd row7h7t32c2zzbfixxoo414zkhul
3rd row7h7t32c2zzbfixxoo414zkhul
4th row7h7t32c2zzbfixxoo414zkhul
5th row7h7t32c2zzbfixxoo414zkhul

Common Values

ValueCountFrequency (%)
7h7t32c2zzbfixxoo414zkhul 56601
100.0%

Length

2024-05-15T13:44:35.821069image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:36.077151image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
7h7t32c2zzbfixxoo414zkhul 56601
100.0%

Most occurring characters

ValueCountFrequency (%)
z 169803
12.0%
7 113202
 
8.0%
x 113202
 
8.0%
2 113202
 
8.0%
4 113202
 
8.0%
h 113202
 
8.0%
o 113202
 
8.0%
u 56601
 
4.0%
k 56601
 
4.0%
1 56601
 
4.0%
Other values (7) 396207
28.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 962217
68.0%
Decimal Number 452808
32.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
z 169803
17.6%
x 113202
11.8%
h 113202
11.8%
o 113202
11.8%
u 56601
 
5.9%
k 56601
 
5.9%
f 56601
 
5.9%
i 56601
 
5.9%
b 56601
 
5.9%
c 56601
 
5.9%
Other values (2) 113202
11.8%
Decimal Number
ValueCountFrequency (%)
7 113202
25.0%
2 113202
25.0%
4 113202
25.0%
1 56601
12.5%
3 56601
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 962217
68.0%
Common 452808
32.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
z 169803
17.6%
x 113202
11.8%
h 113202
11.8%
o 113202
11.8%
u 56601
 
5.9%
k 56601
 
5.9%
f 56601
 
5.9%
i 56601
 
5.9%
b 56601
 
5.9%
c 56601
 
5.9%
Other values (2) 113202
11.8%
Common
ValueCountFrequency (%)
7 113202
25.0%
2 113202
25.0%
4 113202
25.0%
1 56601
12.5%
3 56601
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1415025
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
z 169803
12.0%
7 113202
 
8.0%
x 113202
 
8.0%
2 113202
 
8.0%
4 113202
 
8.0%
h 113202
 
8.0%
o 113202
 
8.0%
u 56601
 
4.0%
k 56601
 
4.0%
1 56601
 
4.0%
Other values (7) 396207
28.0%

platform
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size497.9 KiB
iPhone
50617 
PC
5815 
Android
 
103
Other
 
66

Length

Max length7
Median length6
Mean length5.5897069
Min length2

Characters and Unicode

Total characters316383
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowiPhone
2nd rowiPhone
3rd rowiPhone
4th rowiPhone
5th rowiPhone

Common Values

ValueCountFrequency (%)
iPhone 50617
89.4%
PC 5815
 
10.3%
Android 103
 
0.2%
Other 66
 
0.1%

Length

2024-05-15T13:44:36.342825image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:36.627826image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
iphone 50617
89.4%
pc 5815
 
10.3%
android 103
 
0.2%
other 66
 
0.1%

Most occurring characters

ValueCountFrequency (%)
P 56432
17.8%
i 50720
16.0%
o 50720
16.0%
n 50720
16.0%
h 50683
16.0%
e 50683
16.0%
C 5815
 
1.8%
d 206
 
0.1%
r 169
 
0.1%
A 103
 
< 0.1%
Other values (2) 132
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 253967
80.3%
Uppercase Letter 62416
 
19.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 50720
20.0%
o 50720
20.0%
n 50720
20.0%
h 50683
20.0%
e 50683
20.0%
d 206
 
0.1%
r 169
 
0.1%
t 66
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
P 56432
90.4%
C 5815
 
9.3%
A 103
 
0.2%
O 66
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 316383
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 56432
17.8%
i 50720
16.0%
o 50720
16.0%
n 50720
16.0%
h 50683
16.0%
e 50683
16.0%
C 5815
 
1.8%
d 206
 
0.1%
r 169
 
0.1%
A 103
 
< 0.1%
Other values (2) 132
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 316383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 56432
17.8%
i 50720
16.0%
o 50720
16.0%
n 50720
16.0%
h 50683
16.0%
e 50683
16.0%
C 5815
 
1.8%
d 206
 
0.1%
r 169
 
0.1%
A 103
 
< 0.1%
Other values (2) 132
 
< 0.1%

ms_played
Real number (ℝ)

ZEROS 

Distinct25302
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101844.32
Minimum0
Maximum7737896
Zeros2116
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size884.4 KiB
2024-05-15T13:44:36.922003image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile120
Q12530
median51509
Q3183266
95-th percentile286986
Maximum7737896
Range7737896
Interquartile range (IQR)180736

Descriptive statistics

Standard deviation156520.79
Coefficient of variation (CV)1.5368632
Kurtosis398.35217
Mean101844.32
Median Absolute Deviation (MAD)50959
Skewness13.530629
Sum5.7644905 × 109
Variance2.4498758 × 1010
MonotonicityNot monotonic
2024-05-15T13:44:37.286890image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2116
 
3.7%
69 139
 
0.2%
650 124
 
0.2%
580 115
 
0.2%
789 113
 
0.2%
1160 87
 
0.2%
800 84
 
0.1%
696 82
 
0.1%
810 82
 
0.1%
510 80
 
0.1%
Other values (25292) 53579
94.7%
ValueCountFrequency (%)
0 2116
3.7%
1 57
 
0.1%
5 1
 
< 0.1%
10 5
 
< 0.1%
19 1
 
< 0.1%
20 3
 
< 0.1%
21 23
 
< 0.1%
22 1
 
< 0.1%
23 9
 
< 0.1%
26 1
 
< 0.1%
ValueCountFrequency (%)
7737896 1
< 0.1%
5937706 1
< 0.1%
5779464 1
< 0.1%
5740871 1
< 0.1%
5486144 1
< 0.1%
5137284 1
< 0.1%
5052580 1
< 0.1%
4889664 1
< 0.1%
4779832 1
< 0.1%
4661399 1
< 0.1%

conn_country
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
PL
56599 
BY
 
1
IN
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters113202
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowPL
2nd rowPL
3rd rowPL
4th rowPL
5th rowPL

Common Values

ValueCountFrequency (%)
PL 56599
> 99.9%
BY 1
 
< 0.1%
IN 1
 
< 0.1%

Length

2024-05-15T13:44:37.606391image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:37.826479image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
pl 56599
> 99.9%
by 1
 
< 0.1%
in 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
P 56599
50.0%
L 56599
50.0%
B 1
 
< 0.1%
Y 1
 
< 0.1%
I 1
 
< 0.1%
N 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 113202
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 56599
50.0%
L 56599
50.0%
B 1
 
< 0.1%
Y 1
 
< 0.1%
I 1
 
< 0.1%
N 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 113202
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 56599
50.0%
L 56599
50.0%
B 1
 
< 0.1%
Y 1
 
< 0.1%
I 1
 
< 0.1%
N 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 56599
50.0%
L 56599
50.0%
B 1
 
< 0.1%
Y 1
 
< 0.1%
I 1
 
< 0.1%
N 1
 
< 0.1%
Distinct715
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.2 MiB
2024-05-15T13:44:38.547213image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length15
Median length14
Mean length12.34881
Min length10

Characters and Unicode

Total characters698955
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.1%

Sample

1st row31.60.48.10
2nd row31.60.48.10
3rd row31.60.48.10
4th row31.60.48.10
5th row31.60.48.10
ValueCountFrequency (%)
185.49.31.254 17967
31.7%
193.239.56.126 1873
 
3.3%
83.168.79.18 1635
 
2.9%
212.127.93.94 1103
 
1.9%
188.146.6.53 577
 
1.0%
188.146.130.10 420
 
0.7%
37.30.18.94 388
 
0.7%
188.146.130.173 371
 
0.7%
37.30.114.57 333
 
0.6%
188.146.134.12 296
 
0.5%
Other values (705) 31638
55.9%
2024-05-15T13:44:40.019335image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 169803
24.3%
1 117136
16.8%
3 75283
10.8%
4 54994
 
7.9%
5 49398
 
7.1%
2 44647
 
6.4%
8 44543
 
6.4%
6 43616
 
6.2%
0 41755
 
6.0%
9 35745
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 529152
75.7%
Other Punctuation 169803
 
24.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 117136
22.1%
3 75283
14.2%
4 54994
10.4%
5 49398
9.3%
2 44647
 
8.4%
8 44543
 
8.4%
6 43616
 
8.2%
0 41755
 
7.9%
9 35745
 
6.8%
7 22035
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 169803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 698955
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 169803
24.3%
1 117136
16.8%
3 75283
10.8%
4 54994
 
7.9%
5 49398
 
7.1%
2 44647
 
6.4%
8 44543
 
6.4%
6 43616
 
6.2%
0 41755
 
6.0%
9 35745
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 698955
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 169803
24.3%
1 117136
16.8%
3 75283
10.8%
4 54994
 
7.9%
5 49398
 
7.1%
2 44647
 
6.4%
8 44543
 
6.4%
6 43616
 
6.2%
0 41755
 
6.0%
9 35745
 
5.1%

user_agent_decrypted
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56601
Missing (%)100.0%
Memory size884.4 KiB
Distinct8622
Distinct (%)15.3%
Missing232
Missing (%)0.4%
Memory size4.6 MiB
2024-05-15T13:44:41.165335image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length119
Median length90
Mean length16.157232
Min length1

Characters and Unicode

Total characters910767
Distinct characters224
Distinct categories17 ?
Distinct scripts6 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4076 ?
Unique (%)7.2%

Sample

1st rowIf You Were There, Beware
2nd rowWUJEK DOBRA RADA
3rd rowWUJEK DOBRA RADA
4th rowWYTRAWNE (Z NUTĄ DESPERACJI)
5th rowWYTRAWNE (Z NUTĄ DESPERACJI)
ValueCountFrequency (%)
6620
 
3.9%
the 6346
 
3.7%
you 2688
 
1.6%
i 2238
 
1.3%
a 2082
 
1.2%
in 1753
 
1.0%
remastered 1751
 
1.0%
to 1702
 
1.0%
of 1614
 
1.0%
me 1587
 
0.9%
Other values (7714) 141216
83.3%
2024-05-15T13:44:42.343650image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113228
 
12.4%
e 87759
 
9.6%
a 52044
 
5.7%
o 48795
 
5.4%
i 43426
 
4.8%
t 41966
 
4.6%
n 40414
 
4.4%
r 39478
 
4.3%
s 31822
 
3.5%
l 27717
 
3.0%
Other values (214) 384118
42.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 588943
64.7%
Uppercase Letter 166386
 
18.3%
Space Separator 113228
 
12.4%
Decimal Number 16419
 
1.8%
Other Punctuation 11625
 
1.3%
Dash Punctuation 6451
 
0.7%
Open Punctuation 3550
 
0.4%
Close Punctuation 3548
 
0.4%
Final Punctuation 314
 
< 0.1%
Math Symbol 133
 
< 0.1%
Other values (7) 170
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 87759
14.9%
a 52044
 
8.8%
o 48795
 
8.3%
i 43426
 
7.4%
t 41966
 
7.1%
n 40414
 
6.9%
r 39478
 
6.7%
s 31822
 
5.4%
l 27717
 
4.7%
h 21730
 
3.7%
Other values (75) 153792
26.1%
Uppercase Letter
ValueCountFrequency (%)
T 14165
 
8.5%
S 14042
 
8.4%
A 10756
 
6.5%
M 9575
 
5.8%
I 9435
 
5.7%
W 8700
 
5.2%
L 8575
 
5.2%
R 8563
 
5.1%
B 8101
 
4.9%
O 7762
 
4.7%
Other values (52) 66712
40.1%
Other Letter
ValueCountFrequency (%)
5
 
7.2%
5
 
7.2%
5
 
7.2%
5
 
7.2%
5
 
7.2%
5
 
7.2%
5
 
7.2%
5
 
7.2%
4
 
5.8%
4
 
5.8%
Other values (16) 21
30.4%
Other Punctuation
ValueCountFrequency (%)
' 3479
29.9%
. 2754
23.7%
, 1459
12.6%
? 1341
 
11.5%
# 798
 
6.9%
& 531
 
4.6%
! 379
 
3.3%
/ 306
 
2.6%
" 290
 
2.5%
: 155
 
1.3%
Other values (6) 133
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 4726
28.8%
1 3891
23.7%
2 3811
23.2%
9 1248
 
7.6%
5 858
 
5.2%
8 522
 
3.2%
4 371
 
2.3%
6 353
 
2.1%
7 345
 
2.1%
3 294
 
1.8%
Math Symbol
ValueCountFrequency (%)
+ 92
69.2%
| 24
 
18.0%
> 9
 
6.8%
< 3
 
2.3%
= 2
 
1.5%
2
 
1.5%
1
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 6434
99.7%
11
 
0.2%
6
 
0.1%
Other Symbol
ValueCountFrequency (%)
° 1
33.3%
1
33.3%
® 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3444
97.0%
[ 106
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 3442
97.0%
] 106
 
3.0%
Final Punctuation
ValueCountFrequency (%)
299
95.2%
15
 
4.8%
Space Separator
ValueCountFrequency (%)
113228
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 63
100.0%
Initial Punctuation
ValueCountFrequency (%)
21
100.0%
Modifier Letter
ValueCountFrequency (%)
10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 753203
82.7%
Common 155369
 
17.1%
Cyrillic 2126
 
0.2%
Katakana 57
 
< 0.1%
Han 10
 
< 0.1%
Hiragana 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 87759
 
11.7%
a 52044
 
6.9%
o 48795
 
6.5%
i 43426
 
5.8%
t 41966
 
5.6%
n 40414
 
5.4%
r 39478
 
5.2%
s 31822
 
4.2%
l 27717
 
3.7%
h 21730
 
2.9%
Other values (83) 318052
42.2%
Cyrillic
ValueCountFrequency (%)
е 191
 
9.0%
а 187
 
8.8%
о 185
 
8.7%
и 140
 
6.6%
н 125
 
5.9%
т 119
 
5.6%
к 110
 
5.2%
л 98
 
4.6%
р 88
 
4.1%
с 67
 
3.2%
Other values (44) 816
38.4%
Common
ValueCountFrequency (%)
113228
72.9%
- 6434
 
4.1%
0 4726
 
3.0%
1 3891
 
2.5%
2 3811
 
2.5%
' 3479
 
2.2%
( 3444
 
2.2%
) 3442
 
2.2%
. 2754
 
1.8%
, 1459
 
0.9%
Other values (41) 8701
 
5.6%
Katakana
ValueCountFrequency (%)
5
8.8%
5
8.8%
5
8.8%
5
8.8%
5
8.8%
5
8.8%
5
8.8%
5
8.8%
4
7.0%
4
7.0%
Other values (6) 9
15.8%
Han
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 901740
99.0%
Latin Ext A 5690
 
0.6%
Cyrillic 2126
 
0.2%
Latin 1 Sup 705
 
0.1%
Punctuation 417
 
< 0.1%
Katakana 67
 
< 0.1%
CJK 10
 
< 0.1%
None 6
 
< 0.1%
Math Operators 3
 
< 0.1%
Hiragana 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113228
 
12.6%
e 87759
 
9.7%
a 52044
 
5.8%
o 48795
 
5.4%
i 43426
 
4.8%
t 41966
 
4.7%
n 40414
 
4.5%
r 39478
 
4.4%
s 31822
 
3.5%
l 27717
 
3.1%
Other values (78) 375091
41.6%
Latin Ext A
ValueCountFrequency (%)
ł 1320
23.2%
ś 675
11.9%
ę 656
11.5%
ą 577
10.1%
ż 498
 
8.8%
ć 476
 
8.4%
Ś 295
 
5.2%
Ł 244
 
4.3%
Ą 220
 
3.9%
ń 199
 
3.5%
Other values (10) 530
9.3%
Latin 1 Sup
ValueCountFrequency (%)
ó 434
61.6%
é 122
 
17.3%
Ó 64
 
9.1%
á 30
 
4.3%
ü 11
 
1.6%
í 11
 
1.6%
è 4
 
0.6%
¿ 3
 
0.4%
ö 3
 
0.4%
ñ 2
 
0.3%
Other values (15) 21
 
3.0%
Punctuation
ValueCountFrequency (%)
299
71.7%
67
 
16.1%
21
 
5.0%
15
 
3.6%
11
 
2.6%
4
 
1.0%
Cyrillic
ValueCountFrequency (%)
е 191
 
9.0%
а 187
 
8.8%
о 185
 
8.7%
и 140
 
6.6%
н 125
 
5.9%
т 119
 
5.6%
к 110
 
5.2%
л 98
 
4.6%
р 88
 
4.1%
с 67
 
3.2%
Other values (44) 816
38.4%
Katakana
ValueCountFrequency (%)
10
14.9%
5
 
7.5%
5
 
7.5%
5
 
7.5%
5
 
7.5%
5
 
7.5%
5
 
7.5%
5
 
7.5%
5
 
7.5%
4
 
6.0%
Other values (7) 13
19.4%
None
ValueCountFrequency (%)
6
100.0%
CJK
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Math Operators
ValueCountFrequency (%)
2
66.7%
1
33.3%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%
Distinct3037
Distinct (%)5.4%
Missing232
Missing (%)0.4%
Memory size4.2 MiB
2024-05-15T13:44:43.272135image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length73
Median length42
Mean length11.096436
Min length1

Characters and Unicode

Total characters625495
Distinct characters181
Distinct categories15 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1373 ?
Unique (%)2.4%

Sample

1st rowArctic Monkeys
2nd rowTaco Hemingway
3rd rowTaco Hemingway
4th rowTaco Hemingway
5th rowTaco Hemingway
ValueCountFrequency (%)
the 8105
 
7.9%
arctic 5125
 
5.0%
monkeys 5125
 
5.0%
taco 3737
 
3.6%
hemingway 3737
 
3.6%
weeknd 1870
 
1.8%
strokes 1596
 
1.6%
interpol 1583
 
1.5%
nirvana 1583
 
1.5%
lil 1573
 
1.5%
Other values (4032) 68408
66.8%
2024-05-15T13:44:44.618634image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 61248
 
9.8%
a 47327
 
7.6%
46073
 
7.4%
i 37395
 
6.0%
o 35949
 
5.7%
n 33085
 
5.3%
r 28022
 
4.5%
s 25293
 
4.0%
t 24114
 
3.9%
c 21239
 
3.4%
Other values (171) 265750
42.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 461415
73.8%
Uppercase Letter 112273
 
17.9%
Space Separator 46073
 
7.4%
Decimal Number 3380
 
0.5%
Other Punctuation 1493
 
0.2%
Dash Punctuation 463
 
0.1%
Currency Symbol 162
 
< 0.1%
Math Symbol 99
 
< 0.1%
Other Letter 88
 
< 0.1%
Final Punctuation 12
 
< 0.1%
Other values (5) 37
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 61248
13.3%
a 47327
 
10.3%
i 37395
 
8.1%
o 35949
 
7.8%
n 33085
 
7.2%
r 28022
 
6.1%
s 25293
 
5.5%
t 24114
 
5.2%
c 21239
 
4.6%
l 19836
 
4.3%
Other values (65) 127907
27.7%
Uppercase Letter
ValueCountFrequency (%)
T 15416
13.7%
M 9798
 
8.7%
A 8865
 
7.9%
S 6959
 
6.2%
P 6580
 
5.9%
H 6204
 
5.5%
L 5785
 
5.2%
D 5339
 
4.8%
C 5309
 
4.7%
R 5130
 
4.6%
Other values (42) 36888
32.9%
Other Letter
ValueCountFrequency (%)
10
11.4%
9
10.2%
9
10.2%
9
10.2%
9
10.2%
9
10.2%
9
10.2%
9
10.2%
9
10.2%
1
 
1.1%
Other values (5) 5
5.7%
Decimal Number
ValueCountFrequency (%)
1 785
23.2%
2 563
16.7%
3 509
15.1%
8 483
14.3%
5 368
10.9%
0 235
 
7.0%
4 149
 
4.4%
9 129
 
3.8%
7 118
 
3.5%
6 33
 
1.0%
Other values (4) 8
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 760
50.9%
' 255
 
17.1%
: 158
 
10.6%
& 153
 
10.2%
, 84
 
5.6%
! 45
 
3.0%
? 15
 
1.0%
/ 15
 
1.0%
" 6
 
0.4%
2
 
0.1%
Math Symbol
ValueCountFrequency (%)
| 79
79.8%
+ 10
 
10.1%
< 9
 
9.1%
~ 1
 
1.0%
Currency Symbol
ValueCountFrequency (%)
$ 134
82.7%
¥ 28
 
17.3%
Other Symbol
ValueCountFrequency (%)
5
71.4%
® 2
 
28.6%
Space Separator
ValueCountFrequency (%)
46073
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 463
100.0%
Final Punctuation
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Modifier Letter
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 573164
91.6%
Common 51719
 
8.3%
Cyrillic 524
 
0.1%
Hiragana 45
 
< 0.1%
Katakana 41
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 61248
 
10.7%
a 47327
 
8.3%
i 37395
 
6.5%
o 35949
 
6.3%
n 33085
 
5.8%
r 28022
 
4.9%
s 25293
 
4.4%
t 24114
 
4.2%
c 21239
 
3.7%
l 19836
 
3.5%
Other values (74) 239656
41.8%
Cyrillic
ValueCountFrequency (%)
о 63
 
12.0%
н 47
 
9.0%
е 42
 
8.0%
у 39
 
7.4%
к 39
 
7.4%
р 33
 
6.3%
с 30
 
5.7%
а 28
 
5.3%
й 22
 
4.2%
В 21
 
4.0%
Other values (33) 160
30.5%
Common
ValueCountFrequency (%)
46073
89.1%
1 785
 
1.5%
. 760
 
1.5%
2 563
 
1.1%
3 509
 
1.0%
8 483
 
0.9%
- 463
 
0.9%
5 368
 
0.7%
' 255
 
0.5%
0 235
 
0.5%
Other values (29) 1225
 
2.4%
Katakana
ValueCountFrequency (%)
10
24.4%
9
22.0%
9
22.0%
9
22.0%
1
 
2.4%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Hiragana
ValueCountFrequency (%)
9
20.0%
9
20.0%
9
20.0%
9
20.0%
9
20.0%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 622673
99.5%
Latin Ext A 1660
 
0.3%
Cyrillic 524
 
0.1%
Latin 1 Sup 521
 
0.1%
Hiragana 45
 
< 0.1%
Katakana 43
 
< 0.1%
Punctuation 14
 
< 0.1%
None 8
 
< 0.1%
Dingbats 5
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 61248
 
9.8%
a 47327
 
7.6%
46073
 
7.4%
i 37395
 
6.0%
o 35949
 
5.8%
n 33085
 
5.3%
r 28022
 
4.5%
s 25293
 
4.1%
t 24114
 
3.9%
c 21239
 
3.4%
Other values (71) 262928
42.2%
Latin Ext A
ValueCountFrequency (%)
ł 1320
79.5%
ę 186
 
11.2%
Ł 43
 
2.6%
ś 39
 
2.3%
Ż 21
 
1.3%
Ś 14
 
0.8%
ż 14
 
0.8%
ń 10
 
0.6%
ą 4
 
0.2%
ō 3
 
0.2%
Other values (6) 6
 
0.4%
Latin 1 Sup
ValueCountFrequency (%)
å 281
53.9%
é 79
 
15.2%
ó 51
 
9.8%
¥ 28
 
5.4%
ô 26
 
5.0%
ø 14
 
2.7%
Ø 8
 
1.5%
ö 7
 
1.3%
É 5
 
1.0%
ñ 5
 
1.0%
Other values (8) 17
 
3.3%
Cyrillic
ValueCountFrequency (%)
о 63
 
12.0%
н 47
 
9.0%
е 42
 
8.0%
у 39
 
7.4%
к 39
 
7.4%
р 33
 
6.3%
с 30
 
5.7%
а 28
 
5.3%
й 22
 
4.2%
В 21
 
4.0%
Other values (33) 160
30.5%
Punctuation
ValueCountFrequency (%)
12
85.7%
2
 
14.3%
Katakana
ValueCountFrequency (%)
10
23.3%
9
20.9%
9
20.9%
9
20.9%
2
 
4.7%
1
 
2.3%
1
 
2.3%
1
 
2.3%
1
 
2.3%
Hiragana
ValueCountFrequency (%)
9
20.0%
9
20.0%
9
20.0%
9
20.0%
9
20.0%
Dingbats
ValueCountFrequency (%)
5
100.0%
None
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct5125
Distinct (%)9.1%
Missing232
Missing (%)0.4%
Memory size4.8 MiB
2024-05-15T13:44:45.349757image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length116
Median length74
Mean length16.615054
Min length1

Characters and Unicode

Total characters936574
Distinct characters239
Distinct categories16 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2549 ?
Unique (%)4.5%

Sample

1st rowFavourite Worst Nightmare
2nd rowPOCZTÓWKA Z WWA, LATO '19
3rd rowPOCZTÓWKA Z WWA, LATO '19
4th rowPOCZTÓWKA Z WWA, LATO '19
5th rowPOCZTÓWKA Z WWA, LATO '19
ValueCountFrequency (%)
the 9119
 
5.5%
of 2543
 
1.5%
2441
 
1.5%
am 1986
 
1.2%
on 1971
 
1.2%
it 1885
 
1.1%
1-800-oświecenie 1775
 
1.1%
i 1711
 
1.0%
in 1694
 
1.0%
to 1670
 
1.0%
Other values (5764) 139610
83.9%
2024-05-15T13:44:46.414735image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110036
 
11.7%
e 75339
 
8.0%
a 50105
 
5.3%
o 50072
 
5.3%
r 43292
 
4.6%
t 42474
 
4.5%
i 41986
 
4.5%
n 39896
 
4.3%
s 30213
 
3.2%
h 27322
 
2.9%
Other values (229) 425839
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 594941
63.5%
Uppercase Letter 191923
 
20.5%
Space Separator 110036
 
11.7%
Other Punctuation 16318
 
1.7%
Decimal Number 15023
 
1.6%
Dash Punctuation 4679
 
0.5%
Open Punctuation 1509
 
0.2%
Close Punctuation 1503
 
0.2%
Math Symbol 284
 
< 0.1%
Other Letter 188
 
< 0.1%
Other values (6) 170
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 75339
12.7%
a 50105
 
8.4%
o 50072
 
8.4%
r 43292
 
7.3%
t 42474
 
7.1%
i 41986
 
7.1%
n 39896
 
6.7%
s 30213
 
5.1%
h 27322
 
4.6%
l 25718
 
4.3%
Other values (77) 168524
28.3%
Uppercase Letter
ValueCountFrequency (%)
T 19849
 
10.3%
I 14843
 
7.7%
S 14075
 
7.3%
A 12870
 
6.7%
O 12436
 
6.5%
E 11889
 
6.2%
M 9706
 
5.1%
W 9605
 
5.0%
B 9128
 
4.8%
C 8868
 
4.6%
Other values (54) 68654
35.8%
Other Letter
ValueCountFrequency (%)
25
 
13.3%
11
 
5.9%
11
 
5.9%
11
 
5.9%
11
 
5.9%
11
 
5.9%
9
 
4.8%
9
 
4.8%
9
 
4.8%
9
 
4.8%
Other values (32) 72
38.3%
Other Punctuation
ValueCountFrequency (%)
' 4878
29.9%
. 3724
22.8%
, 3615
22.2%
& 1089
 
6.7%
! 990
 
6.1%
: 608
 
3.7%
? 458
 
2.8%
/ 403
 
2.5%
" 304
 
1.9%
* 193
 
1.2%
Other values (7) 56
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 5294
35.2%
1 3466
23.1%
8 2108
 
14.0%
2 1643
 
10.9%
5 788
 
5.2%
9 735
 
4.9%
4 352
 
2.3%
7 335
 
2.2%
3 164
 
1.1%
6 138
 
0.9%
Math Symbol
ValueCountFrequency (%)
| 152
53.5%
+ 112
39.4%
> 9
 
3.2%
< 7
 
2.5%
÷ 4
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 4677
> 99.9%
2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 1485
98.4%
[ 24
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 1479
98.4%
] 24
 
1.6%
Letter Number
ValueCountFrequency (%)
5
71.4%
2
 
28.6%
Space Separator
ValueCountFrequency (%)
110036
100.0%
Final Punctuation
ValueCountFrequency (%)
105
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 52
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 784413
83.8%
Common 149515
 
16.0%
Cyrillic 2458
 
0.3%
Hiragana 81
 
< 0.1%
Han 55
 
< 0.1%
Katakana 52
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 75339
 
9.6%
a 50105
 
6.4%
o 50072
 
6.4%
r 43292
 
5.5%
t 42474
 
5.4%
i 41986
 
5.4%
n 39896
 
5.1%
s 30213
 
3.9%
h 27322
 
3.5%
l 25718
 
3.3%
Other values (85) 357996
45.6%
Cyrillic
ValueCountFrequency (%)
е 208
 
8.5%
о 202
 
8.2%
и 194
 
7.9%
а 193
 
7.9%
н 178
 
7.2%
т 114
 
4.6%
л 103
 
4.2%
р 90
 
3.7%
с 80
 
3.3%
в 71
 
2.9%
Other values (48) 1025
41.7%
Common
ValueCountFrequency (%)
110036
73.6%
0 5294
 
3.5%
' 4878
 
3.3%
- 4677
 
3.1%
. 3724
 
2.5%
, 3615
 
2.4%
1 3466
 
2.3%
8 2108
 
1.4%
2 1643
 
1.1%
( 1485
 
1.0%
Other values (34) 8589
 
5.7%
Han
ValueCountFrequency (%)
11
20.0%
9
16.4%
9
16.4%
3
 
5.5%
3
 
5.5%
3
 
5.5%
2
 
3.6%
2
 
3.6%
2
 
3.6%
2
 
3.6%
Other values (8) 9
16.4%
Hiragana
ValueCountFrequency (%)
25
30.9%
11
13.6%
11
13.6%
11
13.6%
11
13.6%
3
 
3.7%
3
 
3.7%
2
 
2.5%
1
 
1.2%
1
 
1.2%
Other values (2) 2
 
2.5%
Katakana
ValueCountFrequency (%)
9
17.3%
9
17.3%
9
17.3%
9
17.3%
9
17.3%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%
Other values (2) 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 924692
98.7%
Latin Ext A 7443
 
0.8%
Cyrillic 2458
 
0.3%
Latin 1 Sup 1642
 
0.2%
Punctuation 143
 
< 0.1%
Hiragana 81
 
< 0.1%
CJK 55
 
< 0.1%
Katakana 52
 
< 0.1%
Number Forms 7
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110036
 
11.9%
e 75339
 
8.1%
a 50105
 
5.4%
o 50072
 
5.4%
r 43292
 
4.7%
t 42474
 
4.6%
i 41986
 
4.5%
n 39896
 
4.3%
s 30213
 
3.3%
h 27322
 
3.0%
Other values (76) 413957
44.8%
Latin Ext A
ValueCountFrequency (%)
ł 2241
30.1%
Ś 1829
24.6%
ą 925
12.4%
ę 856
 
11.5%
ś 625
 
8.4%
ć 447
 
6.0%
ż 349
 
4.7%
ń 80
 
1.1%
Ń 28
 
0.4%
Ż 17
 
0.2%
Other values (10) 46
 
0.6%
Latin 1 Sup
ValueCountFrequency (%)
ó 925
56.3%
Ó 359
 
21.9%
é 290
 
17.7%
è 12
 
0.7%
í 10
 
0.6%
ê 8
 
0.5%
á 4
 
0.2%
¿ 4
 
0.2%
÷ 4
 
0.2%
´ 3
 
0.2%
Other values (16) 23
 
1.4%
Cyrillic
ValueCountFrequency (%)
е 208
 
8.5%
о 202
 
8.2%
и 194
 
7.9%
а 193
 
7.9%
н 178
 
7.2%
т 114
 
4.6%
л 103
 
4.2%
р 90
 
3.7%
с 80
 
3.3%
в 71
 
2.9%
Other values (48) 1025
41.7%
Punctuation
ValueCountFrequency (%)
105
73.4%
35
 
24.5%
2
 
1.4%
1
 
0.7%
Hiragana
ValueCountFrequency (%)
25
30.9%
11
13.6%
11
13.6%
11
13.6%
11
13.6%
3
 
3.7%
3
 
3.7%
2
 
2.5%
1
 
1.2%
1
 
1.2%
Other values (2) 2
 
2.5%
CJK
ValueCountFrequency (%)
11
20.0%
9
16.4%
9
16.4%
3
 
5.5%
3
 
5.5%
3
 
5.5%
2
 
3.6%
2
 
3.6%
2
 
3.6%
2
 
3.6%
Other values (8) 9
16.4%
Katakana
ValueCountFrequency (%)
9
17.3%
9
17.3%
9
17.3%
9
17.3%
9
17.3%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%
Other values (2) 2
 
3.8%
Number Forms
ValueCountFrequency (%)
5
71.4%
2
 
28.6%
None
ValueCountFrequency (%)
1
100.0%
Distinct9796
Distinct (%)17.4%
Missing232
Missing (%)0.4%
Memory size5.4 MiB
2024-05-15T13:44:46.894671image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters2029284
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4809 ?
Unique (%)8.5%

Sample

1st rowspotify:track:0idZZsnM7nuSYanlpKTuwV
2nd rowspotify:track:5jumw9HzKWgSruqVgfajuk
3rd rowspotify:track:5jumw9HzKWgSruqVgfajuk
4th rowspotify:track:2Mxs1xRmWFdxtpyRLiFsVM
5th rowspotify:track:2Mxs1xRmWFdxtpyRLiFsVM
ValueCountFrequency (%)
spotify:track:1tumlknunyi1l0eqxrga7g 281
 
0.5%
spotify:track:3xksgykjky0bbquuhryrei 208
 
0.4%
spotify:track:60oy6a1eyz3a4apdbv7lv0 189
 
0.3%
spotify:track:0vrloghcwk3xqy1xnuqjhj 185
 
0.3%
spotify:track:5uwwz5lm5pku6ekshagxok 180
 
0.3%
spotify:track:7i1zanux3ik0qj4paswa3z 174
 
0.3%
spotify:track:5fvd6kxrgo9b3jpmc8opst 173
 
0.3%
spotify:track:0bxe4fqsdd1ot4yubxwapp 160
 
0.3%
spotify:track:5ub7v2cui8xscrrufa4zkb 156
 
0.3%
spotify:track:5xefesfbtlpxzivdnqp22n 152
 
0.3%
Other values (9786) 54511
96.7%
2024-05-15T13:44:47.580778image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 131619
 
6.5%
: 112738
 
5.6%
s 76506
 
3.8%
a 76080
 
3.7%
k 75947
 
3.7%
y 75695
 
3.7%
i 75606
 
3.7%
f 75502
 
3.7%
c 74718
 
3.7%
o 74688
 
3.7%
Other values (53) 1180185
58.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1171960
57.8%
Uppercase Letter 498307
24.6%
Decimal Number 246279
 
12.1%
Other Punctuation 112738
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 131619
 
11.2%
s 76506
 
6.5%
a 76080
 
6.5%
k 75947
 
6.5%
y 75695
 
6.5%
i 75606
 
6.5%
f 75502
 
6.4%
c 74718
 
6.4%
o 74688
 
6.4%
p 74570
 
6.4%
Other values (16) 361029
30.8%
Uppercase Letter
ValueCountFrequency (%)
U 21451
 
4.3%
K 20420
 
4.1%
Y 20320
 
4.1%
A 19919
 
4.0%
R 19777
 
4.0%
O 19710
 
4.0%
M 19703
 
4.0%
P 19596
 
3.9%
C 19540
 
3.9%
H 19515
 
3.9%
Other values (16) 298356
59.9%
Decimal Number
ValueCountFrequency (%)
5 27592
11.2%
0 27364
11.1%
1 27131
11.0%
2 26556
10.8%
7 25856
10.5%
3 25751
10.5%
4 24806
10.1%
6 23672
9.6%
9 18828
7.6%
8 18723
7.6%
Other Punctuation
ValueCountFrequency (%)
: 112738
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1670267
82.3%
Common 359017
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 131619
 
7.9%
s 76506
 
4.6%
a 76080
 
4.6%
k 75947
 
4.5%
y 75695
 
4.5%
i 75606
 
4.5%
f 75502
 
4.5%
c 74718
 
4.5%
o 74688
 
4.5%
p 74570
 
4.5%
Other values (42) 859336
51.4%
Common
ValueCountFrequency (%)
: 112738
31.4%
5 27592
 
7.7%
0 27364
 
7.6%
1 27131
 
7.6%
2 26556
 
7.4%
7 25856
 
7.2%
3 25751
 
7.2%
4 24806
 
6.9%
6 23672
 
6.6%
9 18828
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2029284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 131619
 
6.5%
: 112738
 
5.6%
s 76506
 
3.8%
a 76080
 
3.7%
k 75947
 
3.7%
y 75695
 
3.7%
i 75606
 
3.7%
f 75502
 
3.7%
c 74718
 
3.7%
o 74688
 
3.7%
Other values (53) 1180185
58.2%

episode_name
Text

MISSING 

Distinct145
Distinct (%)62.5%
Missing56369
Missing (%)99.6%
Memory size2.2 MiB
2024-05-15T13:44:48.097857image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length120
Median length69
Mean length48.206897
Min length8

Characters and Unicode

Total characters11184
Distinct characters95
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)42.2%

Sample

1st row10: Porównywanie się z innymi
2nd row10: Porównywanie się z innymi
3rd row9: Mity psychologiczne - 3 na początek
4th rowKsiążka – gwarantowany przepis na sukces
5th rowEpisode #137 ... John Rawls - A Theory of Justice
ValueCountFrequency (%)
191
 
10.1%
epizod 83
 
4.4%
of 38
 
2.0%
the 31
 
1.6%
22
 
1.2%
and 22
 
1.2%
will 16
 
0.8%
mysloᴠitz 15
 
0.8%
ai 15
 
0.8%
why 14
 
0.7%
Other values (717) 1447
76.4%
2024-05-15T13:44:48.856585image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1667
 
14.9%
i 737
 
6.6%
e 719
 
6.4%
a 564
 
5.0%
o 553
 
4.9%
n 455
 
4.1%
t 410
 
3.7%
s 376
 
3.4%
r 355
 
3.2%
l 331
 
3.0%
Other values (85) 5017
44.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6986
62.5%
Space Separator 1667
 
14.9%
Uppercase Letter 1499
 
13.4%
Decimal Number 449
 
4.0%
Other Punctuation 338
 
3.0%
Dash Punctuation 146
 
1.3%
Math Symbol 56
 
0.5%
Open Punctuation 21
 
0.2%
Close Punctuation 21
 
0.2%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 737
 
10.5%
e 719
 
10.3%
a 564
 
8.1%
o 553
 
7.9%
n 455
 
6.5%
t 410
 
5.9%
s 376
 
5.4%
r 355
 
5.1%
l 331
 
4.7%
d 280
 
4.0%
Other values (27) 2206
31.6%
Uppercase Letter
ValueCountFrequency (%)
E 155
 
10.3%
S 117
 
7.8%
A 98
 
6.5%
P 97
 
6.5%
T 80
 
5.3%
D 79
 
5.3%
I 78
 
5.2%
C 76
 
5.1%
W 76
 
5.1%
R 70
 
4.7%
Other values (20) 573
38.2%
Decimal Number
ValueCountFrequency (%)
1 109
24.3%
2 84
18.7%
0 51
11.4%
3 42
 
9.4%
5 37
 
8.2%
4 33
 
7.3%
7 25
 
5.6%
8 24
 
5.3%
9 24
 
5.3%
6 20
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 96
28.4%
# 66
19.5%
? 44
13.0%
. 38
 
11.2%
: 37
 
10.9%
& 24
 
7.1%
' 20
 
5.9%
! 11
 
3.3%
" 2
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 124
84.9%
22
 
15.1%
Open Punctuation
ValueCountFrequency (%)
( 20
95.2%
[ 1
 
4.8%
Close Punctuation
ValueCountFrequency (%)
) 20
95.2%
] 1
 
4.8%
Space Separator
ValueCountFrequency (%)
1667
100.0%
Math Symbol
ValueCountFrequency (%)
| 56
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8485
75.9%
Common 2699
 
24.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 737
 
8.7%
e 719
 
8.5%
a 564
 
6.6%
o 553
 
6.5%
n 455
 
5.4%
t 410
 
4.8%
s 376
 
4.4%
r 355
 
4.2%
l 331
 
3.9%
d 280
 
3.3%
Other values (57) 3705
43.7%
Common
ValueCountFrequency (%)
1667
61.8%
- 124
 
4.6%
1 109
 
4.0%
, 96
 
3.6%
2 84
 
3.1%
# 66
 
2.4%
| 56
 
2.1%
0 51
 
1.9%
? 44
 
1.6%
3 42
 
1.6%
Other values (18) 360
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10976
98.1%
Latin Ext A 152
 
1.4%
Punctuation 23
 
0.2%
Latin 1 Sup 18
 
0.2%
Phonetic Ext 15
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1667
 
15.2%
i 737
 
6.7%
e 719
 
6.6%
a 564
 
5.1%
o 553
 
5.0%
n 455
 
4.1%
t 410
 
3.7%
s 376
 
3.4%
r 355
 
3.2%
l 331
 
3.0%
Other values (67) 4809
43.8%
Latin Ext A
ValueCountFrequency (%)
ł 59
38.8%
ę 24
15.8%
ą 18
 
11.8%
ś 11
 
7.2%
ń 10
 
6.6%
ż 9
 
5.9%
Ł 5
 
3.3%
ć 5
 
3.3%
Ę 3
 
2.0%
ź 2
 
1.3%
Other values (4) 6
 
3.9%
Punctuation
ValueCountFrequency (%)
22
95.7%
1
 
4.3%
Latin 1 Sup
ValueCountFrequency (%)
ó 18
100.0%
Phonetic Ext
ValueCountFrequency (%)
15
100.0%

episode_show_name
Categorical

MISSING 

Distinct26
Distinct (%)11.2%
Missing56369
Missing (%)99.6%
Memory size3.5 MiB
Dwóch Typów Podcast
83 
Within Reason
39 
Lex Fridman Podcast
20 
Dwarkesh Podcast
15 
Transporter żwiru i piasku
15 
Other values (21)
60 

Length

Max length84
Median length75
Mean length19.784483
Min length8

Characters and Unicode

Total characters4590
Distinct characters76
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)5.6%

Sample

1st rowPsychologia, którą warto znać
2nd rowPsychologia, którą warto znać
3rd rowPsychologia, którą warto znać
4th rowNauka To Lubię
5th rowPhilosophize This!

Common Values

ValueCountFrequency (%)
Dwóch Typów Podcast 83
 
0.1%
Within Reason 39
 
0.1%
Lex Fridman Podcast 20
 
< 0.1%
Dwarkesh Podcast 15
 
< 0.1%
Transporter żwiru i piasku 15
 
< 0.1%
𝑻𝑹𝑨𝑪𝑬𝑴𝑶𝑵𝑲𝑬𝒀𝑺 14
 
< 0.1%
Waveform: The MKBHD Podcast 11
 
< 0.1%
Skądinąd 7
 
< 0.1%
John Kennedy's Track by Track Podcast 5
 
< 0.1%
Psychologia, którą warto znać 3
 
< 0.1%
Other values (16) 20
 
< 0.1%
(Missing) 56369
99.6%

Length

2024-05-15T13:44:49.073577image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
podcast 139
19.9%
dwóch 83
 
11.9%
typów 83
 
11.9%
within 39
 
5.6%
reason 39
 
5.6%
lex 20
 
2.9%
fridman 20
 
2.9%
i 15
 
2.1%
piasku 15
 
2.1%
the 15
 
2.1%
Other values (78) 231
33.0%

Most occurring characters

ValueCountFrequency (%)
467
 
10.2%
a 325
 
7.1%
c 257
 
5.6%
s 257
 
5.6%
o 238
 
5.2%
t 226
 
4.9%
w 204
 
4.4%
i 200
 
4.4%
d 192
 
4.2%
h 183
 
4.0%
Other values (66) 2041
44.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3284
71.5%
Uppercase Letter 800
 
17.4%
Space Separator 467
 
10.2%
Other Punctuation 26
 
0.6%
Math Symbol 8
 
0.2%
Dash Punctuation 3
 
0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 147
18.4%
T 131
16.4%
D 112
14.0%
W 52
 
6.5%
R 42
 
5.2%
𝑬 28
 
3.5%
L 25
 
3.1%
F 20
 
2.5%
S 17
 
2.1%
K 17
 
2.1%
Other values (23) 209
26.1%
Lowercase Letter
ValueCountFrequency (%)
a 325
 
9.9%
c 257
 
7.8%
s 257
 
7.8%
o 238
 
7.2%
t 226
 
6.9%
w 204
 
6.2%
i 200
 
6.1%
d 192
 
5.8%
h 183
 
5.6%
n 180
 
5.5%
Other values (22) 1022
31.1%
Other Punctuation
ValueCountFrequency (%)
: 14
53.8%
' 5
 
19.2%
, 3
 
11.5%
. 2
 
7.7%
& 1
 
3.8%
! 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
0 1
50.0%
Space Separator
ValueCountFrequency (%)
467
100.0%
Math Symbol
ValueCountFrequency (%)
| 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3916
85.3%
Common 674
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 325
 
8.3%
c 257
 
6.6%
s 257
 
6.6%
o 238
 
6.1%
t 226
 
5.8%
w 204
 
5.2%
i 200
 
5.1%
d 192
 
4.9%
h 183
 
4.7%
n 180
 
4.6%
Other values (44) 1654
42.2%
Common
ValueCountFrequency (%)
467
69.3%
𝑬 28
 
4.2%
: 14
 
2.1%
𝑺 14
 
2.1%
𝑨 14
 
2.1%
𝑹 14
 
2.1%
𝑲 14
 
2.1%
𝑵 14
 
2.1%
𝑶 14
 
2.1%
𝑴 14
 
2.1%
Other values (12) 67
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4208
91.7%
Latin 1 Sup 169
 
3.7%
Math Alphanum 168
 
3.7%
Latin Ext A 45
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
467
 
11.1%
a 325
 
7.7%
c 257
 
6.1%
s 257
 
6.1%
o 238
 
5.7%
t 226
 
5.4%
w 204
 
4.8%
i 200
 
4.8%
d 192
 
4.6%
h 183
 
4.3%
Other values (48) 1659
39.4%
Latin 1 Sup
ValueCountFrequency (%)
ó 169
100.0%
Math Alphanum
ValueCountFrequency (%)
𝑬 28
16.7%
𝑺 14
8.3%
𝑨 14
8.3%
𝑹 14
8.3%
𝑲 14
8.3%
𝑵 14
8.3%
𝑶 14
8.3%
𝑴 14
8.3%
𝑻 14
8.3%
𝑪 14
8.3%
Latin Ext A
ValueCountFrequency (%)
ż 18
40.0%
ą 17
37.8%
ś 3
 
6.7%
ł 3
 
6.7%
ć 3
 
6.7%
ę 1
 
2.2%

spotify_episode_uri
Text

MISSING 

Distinct145
Distinct (%)62.5%
Missing56369
Missing (%)99.6%
Memory size2.2 MiB
2024-05-15T13:44:49.405805image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length38
Median length38
Mean length38
Min length38

Characters and Unicode

Total characters8816
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)42.2%

Sample

1st rowspotify:episode:2qcBNrUIKoVchZLl4raiUN
2nd rowspotify:episode:2qcBNrUIKoVchZLl4raiUN
3rd rowspotify:episode:2ckUNh8AMRQRNTzDr402bj
4th rowspotify:episode:3R0Ojdn4E0u7FuhE2NhcJU
5th rowspotify:episode:7zOrFlyvd3yySVpZb5DmNh
ValueCountFrequency (%)
spotify:episode:7lfwgn4kvozmn4a89zxue3 10
 
4.3%
spotify:episode:2relmi3uikfthyfkzytbne 6
 
2.6%
spotify:episode:43s9st783m6c1tmh3otq4s 5
 
2.2%
spotify:episode:3k2eez30domanzjpmmedjf 5
 
2.2%
spotify:episode:1tfqrjjd8forewkdigm0j9 4
 
1.7%
spotify:episode:3fwlnlr4r2mhfskiw1zirt 4
 
1.7%
spotify:episode:3zoezbiuwckyeqslls7dha 4
 
1.7%
spotify:episode:4oawnpnmaiy3ydvjmn3z8v 4
 
1.7%
spotify:episode:4x2aodml7zdnfrgqmzdlgv 3
 
1.3%
spotify:episode:65grmunkfohjtszqlnxi9b 3
 
1.3%
Other values (135) 184
79.3%
2024-05-15T13:44:49.923154image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 547
 
6.2%
i 543
 
6.2%
s 531
 
6.0%
e 530
 
6.0%
p 513
 
5.8%
: 464
 
5.3%
y 323
 
3.7%
d 314
 
3.6%
f 306
 
3.5%
t 300
 
3.4%
Other values (53) 4445
50.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5283
59.9%
Uppercase Letter 2013
 
22.8%
Decimal Number 1056
 
12.0%
Other Punctuation 464
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 547
10.4%
i 543
10.3%
s 531
10.1%
e 530
10.0%
p 513
9.7%
y 323
 
6.1%
d 314
 
5.9%
f 306
 
5.8%
t 300
 
5.7%
n 121
 
2.3%
Other values (16) 1255
23.8%
Uppercase Letter
ValueCountFrequency (%)
Z 105
 
5.2%
L 101
 
5.0%
U 95
 
4.7%
S 93
 
4.6%
K 92
 
4.6%
J 90
 
4.5%
W 90
 
4.5%
M 85
 
4.2%
N 85
 
4.2%
C 82
 
4.1%
Other values (16) 1095
54.4%
Decimal Number
ValueCountFrequency (%)
3 160
15.2%
4 135
12.8%
7 121
11.5%
0 121
11.5%
1 99
9.4%
2 91
8.6%
9 87
8.2%
5 85
8.0%
8 79
7.5%
6 78
7.4%
Other Punctuation
ValueCountFrequency (%)
: 464
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7296
82.8%
Common 1520
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 547
 
7.5%
i 543
 
7.4%
s 531
 
7.3%
e 530
 
7.3%
p 513
 
7.0%
y 323
 
4.4%
d 314
 
4.3%
f 306
 
4.2%
t 300
 
4.1%
n 121
 
1.7%
Other values (42) 3268
44.8%
Common
ValueCountFrequency (%)
: 464
30.5%
3 160
 
10.5%
4 135
 
8.9%
7 121
 
8.0%
0 121
 
8.0%
1 99
 
6.5%
2 91
 
6.0%
9 87
 
5.7%
5 85
 
5.6%
8 79
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 547
 
6.2%
i 543
 
6.2%
s 531
 
6.0%
e 530
 
6.0%
p 513
 
5.8%
: 464
 
5.3%
y 323
 
3.7%
d 314
 
3.6%
f 306
 
3.5%
t 300
 
3.4%
Other values (53) 4445
50.4%

reason_start
Categorical

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.9 MiB
clickrow
18265 
trackdone
17215 
fwdbtn
16714 
playbtn
1990 
backbtn
 
1476
Other values (3)
 
941

Length

Max length10
Median length9
Mean length7.6340524
Min length6

Characters and Unicode

Total characters432095
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtrackdone
2nd rowclickrow
3rd rowtrackdone
4th rowclickrow
5th rowfwdbtn

Common Values

ValueCountFrequency (%)
clickrow 18265
32.3%
trackdone 17215
30.4%
fwdbtn 16714
29.5%
playbtn 1990
 
3.5%
backbtn 1476
 
2.6%
appload 700
 
1.2%
remote 204
 
0.4%
trackerror 37
 
0.1%

Length

2024-05-15T13:44:50.167760image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:50.380756image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
clickrow 18265
32.3%
trackdone 17215
30.4%
fwdbtn 16714
29.5%
playbtn 1990
 
3.5%
backbtn 1476
 
2.6%
appload 700
 
1.2%
remote 204
 
0.4%
trackerror 37
 
0.1%

Most occurring characters

ValueCountFrequency (%)
c 55258
12.8%
t 37636
8.7%
n 37395
8.7%
k 36993
8.6%
o 36421
8.4%
r 35832
8.3%
w 34979
8.1%
d 34629
8.0%
a 22118
 
5.1%
b 21656
 
5.0%
Other values (7) 79178
18.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 432095
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 55258
12.8%
t 37636
8.7%
n 37395
8.7%
k 36993
8.6%
o 36421
8.4%
r 35832
8.3%
w 34979
8.1%
d 34629
8.0%
a 22118
 
5.1%
b 21656
 
5.0%
Other values (7) 79178
18.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 432095
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 55258
12.8%
t 37636
8.7%
n 37395
8.7%
k 36993
8.6%
o 36421
8.4%
r 35832
8.3%
w 34979
8.1%
d 34629
8.0%
a 22118
 
5.1%
b 21656
 
5.0%
Other values (7) 79178
18.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432095
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 55258
12.8%
t 37636
8.7%
n 37395
8.7%
k 36993
8.6%
o 36421
8.4%
r 35832
8.3%
w 34979
8.1%
d 34629
8.0%
a 22118
 
5.1%
b 21656
 
5.0%
Other values (7) 79178
18.3%

reason_end
Categorical

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.9 MiB
endplay
19443 
trackdone
16894 
fwdbtn
16637 
backbtn
 
1475
unexpected-exit-while-paused
 
1047
Other values (5)
 
1105

Length

Max length28
Median length15
Mean length7.6767372
Min length6

Characters and Unicode

Total characters434511
Distinct characters23
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowunexpected-exit-while-paused
2nd rowtrackdone
3rd rowendplay
4th rowfwdbtn
5th rowfwdbtn

Common Values

ValueCountFrequency (%)
endplay 19443
34.4%
trackdone 16894
29.8%
fwdbtn 16637
29.4%
backbtn 1475
 
2.6%
unexpected-exit-while-paused 1047
 
1.8%
logout 781
 
1.4%
remote 247
 
0.4%
unknown 49
 
0.1%
unexpected-exit 22
 
< 0.1%
trackerror 6
 
< 0.1%

Length

2024-05-15T13:44:50.592081image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:50.770163image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
endplay 19443
34.4%
trackdone 16894
29.8%
fwdbtn 16637
29.4%
backbtn 1475
 
2.6%
unexpected-exit-while-paused 1047
 
1.8%
logout 781
 
1.4%
remote 247
 
0.4%
unknown 49
 
0.1%
unexpected-exit 22
 
< 0.1%
trackerror 6
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
n 55665
12.8%
d 55090
12.7%
e 43207
9.9%
a 38865
 
8.9%
t 38178
 
8.8%
p 21559
 
5.0%
l 21271
 
4.9%
b 19587
 
4.5%
c 19444
 
4.5%
y 19443
 
4.5%
Other values (13) 102202
23.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 431348
99.3%
Dash Punctuation 3163
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 55665
12.9%
d 55090
12.8%
e 43207
10.0%
a 38865
 
9.0%
t 38178
 
8.9%
p 21559
 
5.0%
l 21271
 
4.9%
b 19587
 
4.5%
c 19444
 
4.5%
y 19443
 
4.5%
Other values (12) 99039
23.0%
Dash Punctuation
ValueCountFrequency (%)
- 3163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 431348
99.3%
Common 3163
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 55665
12.9%
d 55090
12.8%
e 43207
10.0%
a 38865
 
9.0%
t 38178
 
8.9%
p 21559
 
5.0%
l 21271
 
4.9%
b 19587
 
4.5%
c 19444
 
4.5%
y 19443
 
4.5%
Other values (12) 99039
23.0%
Common
ValueCountFrequency (%)
- 3163
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 434511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 55665
12.8%
d 55090
12.7%
e 43207
9.9%
a 38865
 
8.9%
t 38178
 
8.8%
p 21559
 
5.0%
l 21271
 
4.9%
b 19587
 
4.5%
c 19444
 
4.5%
y 19443
 
4.5%
Other values (13) 102202
23.5%

shuffle
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
0
31065 
1
25536 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters56601
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 31065
54.9%
1 25536
45.1%

Length

2024-05-15T13:44:50.983210image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:51.131212image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
0 31065
54.9%
1 25536
45.1%

Most occurring characters

ValueCountFrequency (%)
0 31065
54.9%
1 25536
45.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56601
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31065
54.9%
1 25536
45.1%

Most occurring scripts

ValueCountFrequency (%)
Common 56601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31065
54.9%
1 25536
45.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31065
54.9%
1 25536
45.1%

skipped
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
1
37555 
0
19046 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters56601
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 37555
66.4%
0 19046
33.6%

Length

2024-05-15T13:44:51.287892image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:51.428893image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
1 37555
66.4%
0 19046
33.6%

Most occurring characters

ValueCountFrequency (%)
1 37555
66.4%
0 19046
33.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56601
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37555
66.4%
0 19046
33.6%

Most occurring scripts

ValueCountFrequency (%)
Common 56601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37555
66.4%
0 19046
33.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 37555
66.4%
0 19046
33.6%

offline
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size497.5 KiB
False
56087 
True
 
514
ValueCountFrequency (%)
False 56087
99.1%
True 514
 
0.9%
2024-05-15T13:44:51.567881image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

offline_timestamp
Real number (ℝ)

Distinct53231
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6849859 × 109
Minimum0
Maximum1.7110487 × 109
Zeros177
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size884.4 KiB
2024-05-15T13:44:51.742877image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.6685011 × 109
Q11.6795739 × 109
median1.6899805 × 109
Q31.7026004 × 109
95-th percentile1.7088148 × 109
Maximum1.7110487 × 109
Range1.7110487 × 109
Interquartile range (IQR)23026437

Descriptive statistics

Standard deviation95254963
Coefficient of variation (CV)0.056531607
Kurtosis303.22357
Mean1.6849859 × 109
Median Absolute Deviation (MAD)11183588
Skewness-17.307068
Sum9.5371889 × 1013
Variance9.073508 × 1015
MonotonicityNot monotonic
2024-05-15T13:44:51.962875image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 177
 
0.3%
1707322900 23
 
< 0.1%
1707322899 22
 
< 0.1%
1707322908 21
 
< 0.1%
1707322910 21
 
< 0.1%
1707322909 20
 
< 0.1%
1707322898 19
 
< 0.1%
1707322901 18
 
< 0.1%
1707323633 17
 
< 0.1%
1707348515 17
 
< 0.1%
Other values (53221) 56246
99.4%
ValueCountFrequency (%)
0 177
0.3%
1665778696 1
 
< 0.1%
1665826304 1
 
< 0.1%
1665826465 1
 
< 0.1%
1665826485 1
 
< 0.1%
1665826697 1
 
< 0.1%
1665826698 1
 
< 0.1%
1665826702 1
 
< 0.1%
1665826706 1
 
< 0.1%
1665826707 1
 
< 0.1%
ValueCountFrequency (%)
1711048721 1
< 0.1%
1711048718 1
< 0.1%
1711048696 1
< 0.1%
1711048476 1
< 0.1%
1711048475 1
< 0.1%
1711048376 1
< 0.1%
1711048251 1
< 0.1%
1711048248 1
< 0.1%
1711048245 1
< 0.1%
1711048165 1
< 0.1%

incognito_mode
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size497.5 KiB
False
56600 
True
 
1
ValueCountFrequency (%)
False 56600
> 99.9%
True 1
 
< 0.1%
2024-05-15T13:44:52.137881image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

hour
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.933411
Minimum0
Maximum23
Zeros2338
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size663.3 KiB
2024-05-15T13:44:52.271800image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median14
Q319
95-th percentile23
Maximum23
Range23
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.9754948
Coefficient of variation (CV)0.42886087
Kurtosis-0.20309437
Mean13.933411
Median Absolute Deviation (MAD)4
Skewness-0.52471212
Sum788645
Variance35.706538
MonotonicityNot monotonic
2024-05-15T13:44:52.434800image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12 3951
 
7.0%
14 3901
 
6.9%
13 3745
 
6.6%
16 3661
 
6.5%
11 3511
 
6.2%
23 3305
 
5.8%
15 3235
 
5.7%
19 3006
 
5.3%
22 2977
 
5.3%
18 2862
 
5.1%
Other values (14) 22447
39.7%
ValueCountFrequency (%)
0 2338
4.1%
1 1192
2.1%
2 769
 
1.4%
3 217
 
0.4%
4 89
 
0.2%
5 353
 
0.6%
6 382
 
0.7%
7 1448
2.6%
8 2386
4.2%
9 2541
4.5%
ValueCountFrequency (%)
23 3305
5.8%
22 2977
5.3%
21 2640
4.7%
20 2701
4.8%
19 3006
5.3%
18 2862
5.1%
17 2688
4.7%
16 3661
6.5%
15 3235
5.7%
14 3901
6.9%

time_of_day
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.2 MiB
noc
24896 
środek dnia
11457 
po południu
10371 
zachód słońca
5300 
rano
4443 

Length

Max length13
Median length11
Mean length7.1237257
Min length3

Characters and Unicode

Total characters403210
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownoc
2nd rowśrodek dnia
3rd rowśrodek dnia
4th rowśrodek dnia
5th rowśrodek dnia

Common Values

ValueCountFrequency (%)
noc 24896
44.0%
środek dnia 11457
20.2%
po południu 10371
18.3%
zachód słońca 5300
 
9.4%
rano 4443
 
7.8%
wschód słońca 134
 
0.2%

Length

2024-05-15T13:44:52.609882image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:52.788782image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
noc 24896
29.7%
środek 11457
13.7%
dnia 11457
13.7%
po 10371
12.4%
południu 10371
12.4%
słońca 5434
 
6.5%
zachód 5300
 
6.3%
rano 4443
 
5.3%
wschód 134
 
0.2%

Most occurring characters

ValueCountFrequency (%)
o 66972
16.6%
n 51167
12.7%
d 38719
9.6%
c 35764
8.9%
27262
 
6.8%
a 26634
 
6.6%
i 21828
 
5.4%
p 20742
 
5.1%
u 20742
 
5.1%
r 15900
 
3.9%
Other values (10) 77480
19.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 375948
93.2%
Space Separator 27262
 
6.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 66972
17.8%
n 51167
13.6%
d 38719
10.3%
c 35764
9.5%
a 26634
 
7.1%
i 21828
 
5.8%
p 20742
 
5.5%
u 20742
 
5.5%
r 15900
 
4.2%
ł 15805
 
4.2%
Other values (9) 61675
16.4%
Space Separator
ValueCountFrequency (%)
27262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 375948
93.2%
Common 27262
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 66972
17.8%
n 51167
13.6%
d 38719
10.3%
c 35764
9.5%
a 26634
 
7.1%
i 21828
 
5.8%
p 20742
 
5.5%
u 20742
 
5.5%
r 15900
 
4.2%
ł 15805
 
4.2%
Other values (9) 61675
16.4%
Common
ValueCountFrequency (%)
27262
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 365080
90.5%
Latin Ext A 32696
 
8.1%
Latin 1 Sup 5434
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 66972
18.3%
n 51167
14.0%
d 38719
10.6%
c 35764
9.8%
27262
7.5%
a 26634
 
7.3%
i 21828
 
6.0%
p 20742
 
5.7%
u 20742
 
5.7%
r 15900
 
4.4%
Other values (6) 39350
10.8%
Latin Ext A
ValueCountFrequency (%)
ł 15805
48.3%
ś 11457
35.0%
ń 5434
 
16.6%
Latin 1 Sup
ValueCountFrequency (%)
ó 5434
100.0%

play_count
Real number (ℝ)

ZEROS 

Distinct281
Distinct (%)0.5%
Missing232
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean17.205219
Minimum0
Maximum280
Zeros9796
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size884.4 KiB
2024-05-15T13:44:53.015240image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q322
95-th percentile68
Maximum280
Range280
Interquartile range (IQR)21

Descriptive statistics

Standard deviation26.49307
Coefficient of variation (CV)1.5398275
Kurtosis15.286928
Mean17.205219
Median Absolute Deviation (MAD)7
Skewness3.2440877
Sum969841
Variance701.88277
MonotonicityNot monotonic
2024-05-15T13:44:53.226217image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9796
 
17.3%
1 4987
 
8.8%
2 3488
 
6.2%
3 2759
 
4.9%
4 2323
 
4.1%
5 2018
 
3.6%
6 1814
 
3.2%
7 1625
 
2.9%
8 1472
 
2.6%
9 1338
 
2.4%
Other values (271) 24749
43.7%
ValueCountFrequency (%)
0 9796
17.3%
1 4987
8.8%
2 3488
 
6.2%
3 2759
 
4.9%
4 2323
 
4.1%
5 2018
 
3.6%
6 1814
 
3.2%
7 1625
 
2.9%
8 1472
 
2.6%
9 1338
 
2.4%
ValueCountFrequency (%)
280 1
< 0.1%
279 1
< 0.1%
278 1
< 0.1%
277 1
< 0.1%
276 1
< 0.1%
275 1
< 0.1%
274 1
< 0.1%
273 1
< 0.1%
272 1
< 0.1%
271 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
1
30282 
0
26319 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters56601
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1 30282
53.5%
0 26319
46.5%

Length

2024-05-15T13:44:53.426194image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:53.568189image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
1 30282
53.5%
0 26319
46.5%

Most occurring characters

ValueCountFrequency (%)
1 30282
53.5%
0 26319
46.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56601
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 30282
53.5%
0 26319
46.5%

Most occurring scripts

ValueCountFrequency (%)
Common 56601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 30282
53.5%
0 26319
46.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 30282
53.5%
0 26319
46.5%

album_play_count
Real number (ℝ)

ZEROS 

Distinct1775
Distinct (%)3.1%
Missing232
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean133.39543
Minimum0
Maximum1774
Zeros5125
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size884.4 KiB
2024-05-15T13:44:53.897189image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median38
Q3145
95-th percentile645
Maximum1774
Range1774
Interquartile range (IQR)139

Descriptive statistics

Standard deviation243.42596
Coefficient of variation (CV)1.8248448
Kurtosis12.93001
Mean133.39543
Median Absolute Deviation (MAD)37
Skewness3.3259864
Sum7519367
Variance59256.198
MonotonicityNot monotonic
2024-05-15T13:44:54.114703image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5125
 
9.1%
1 2576
 
4.6%
2 1813
 
3.2%
3 1430
 
2.5%
4 1188
 
2.1%
5 1045
 
1.8%
6 949
 
1.7%
7 869
 
1.5%
8 803
 
1.4%
9 744
 
1.3%
Other values (1765) 39827
70.4%
ValueCountFrequency (%)
0 5125
9.1%
1 2576
4.6%
2 1813
 
3.2%
3 1430
 
2.5%
4 1188
 
2.1%
5 1045
 
1.8%
6 949
 
1.7%
7 869
 
1.5%
8 803
 
1.4%
9 744
 
1.3%
ValueCountFrequency (%)
1774 1
< 0.1%
1773 1
< 0.1%
1772 1
< 0.1%
1771 1
< 0.1%
1770 1
< 0.1%
1769 1
< 0.1%
1768 1
< 0.1%
1767 1
< 0.1%
1766 1
< 0.1%
1765 1
< 0.1%

artist_play_count
Real number (ℝ)

ZEROS 

Distinct5125
Distinct (%)9.1%
Missing232
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean580.8243
Minimum0
Maximum5124
Zeros3037
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size884.4 KiB
2024-05-15T13:44:54.323701image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median148
Q3678
95-th percentile3021
Maximum5124
Range5124
Interquartile range (IQR)658

Descriptive statistics

Standard deviation973.7159
Coefficient of variation (CV)1.676438
Kurtosis5.9627819
Mean580.8243
Median Absolute Deviation (MAD)145
Skewness2.4618308
Sum32740485
Variance948122.66
MonotonicityNot monotonic
2024-05-15T13:44:54.535704image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3037
 
5.4%
1 1664
 
2.9%
2 1202
 
2.1%
3 940
 
1.7%
4 785
 
1.4%
5 684
 
1.2%
6 622
 
1.1%
7 567
 
1.0%
8 516
 
0.9%
9 479
 
0.8%
Other values (5115) 45873
81.0%
ValueCountFrequency (%)
0 3037
5.4%
1 1664
2.9%
2 1202
 
2.1%
3 940
 
1.7%
4 785
 
1.4%
5 684
 
1.2%
6 622
 
1.1%
7 567
 
1.0%
8 516
 
0.9%
9 479
 
0.8%
ValueCountFrequency (%)
5124 1
< 0.1%
5123 1
< 0.1%
5122 1
< 0.1%
5121 1
< 0.1%
5120 1
< 0.1%
5119 1
< 0.1%
5118 1
< 0.1%
5117 1
< 0.1%
5116 1
< 0.1%
5115 1
< 0.1%

artist_skip_rate_so_far
Real number (ℝ)

ZEROS 

Distinct24044
Distinct (%)42.7%
Missing232
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.65497311
Minimum0
Maximum1
Zeros1631
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size884.4 KiB
2024-05-15T13:44:54.738725image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.33333333
Q10.59090909
median0.65748528
Q30.74468085
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.15377176

Descriptive statistics

Standard deviation0.19628516
Coefficient of variation (CV)0.29968431
Kurtosis2.3727019
Mean0.65497311
Median Absolute Deviation (MAD)0.074876586
Skewness-0.87866408
Sum36920.179
Variance0.038527866
MonotonicityNot monotonic
2024-05-15T13:44:54.953704image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4566
 
8.1%
0 1631
 
2.9%
0.5 1250
 
2.2%
0.6666666667 1146
 
2.0%
0.75 766
 
1.4%
0.8 523
 
0.9%
0.6 397
 
0.7%
0.8333333333 382
 
0.7%
0.3333333333 359
 
0.6%
0.7142857143 335
 
0.6%
Other values (24034) 45014
79.5%
ValueCountFrequency (%)
0 1631
2.9%
0.0303030303 1
 
< 0.1%
0.03448275862 1
 
< 0.1%
0.03571428571 1
 
< 0.1%
0.03703703704 1
 
< 0.1%
0.03846153846 1
 
< 0.1%
0.03921568627 1
 
< 0.1%
0.04 2
 
< 0.1%
0.04081632653 1
 
< 0.1%
0.04166666667 2
 
< 0.1%
ValueCountFrequency (%)
1 4566
8.1%
0.9964412811 1
 
< 0.1%
0.9964285714 1
 
< 0.1%
0.9964157706 1
 
< 0.1%
0.9964028777 1
 
< 0.1%
0.9963898917 1
 
< 0.1%
0.9963768116 1
 
< 0.1%
0.9963636364 1
 
< 0.1%
0.996350365 1
 
< 0.1%
0.9963369963 1
 
< 0.1%

previous_skipped
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
1
37554 
0
19047 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters56601
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 37554
66.3%
0 19047
33.7%

Length

2024-05-15T13:44:55.139701image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T13:44:55.271707image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
1 37554
66.3%
0 19047
33.7%

Most occurring characters

ValueCountFrequency (%)
1 37554
66.3%
0 19047
33.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56601
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37554
66.3%
0 19047
33.7%

Most occurring scripts

ValueCountFrequency (%)
Common 56601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37554
66.3%
0 19047
33.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 37554
66.3%
0 19047
33.7%

current_listening_streak
Real number (ℝ)

ZEROS 

Distinct74
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4676949
Minimum0
Maximum73
Zeros37555
Zeros (%)66.4%
Negative0
Negative (%)0.0%
Memory size884.4 KiB
2024-05-15T13:44:55.432168image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum73
Range73
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.5023103
Coefficient of variation (CV)3.0676064
Kurtosis70.750198
Mean1.4676949
Median Absolute Deviation (MAD)0
Skewness7.1967346
Sum83073
Variance20.270798
MonotonicityNot monotonic
2024-05-15T13:44:55.639935image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37555
66.4%
1 7547
 
13.3%
2 3411
 
6.0%
3 1949
 
3.4%
4 1289
 
2.3%
5 896
 
1.6%
6 669
 
1.2%
7 524
 
0.9%
8 434
 
0.8%
9 338
 
0.6%
Other values (64) 1989
 
3.5%
ValueCountFrequency (%)
0 37555
66.4%
1 7547
 
13.3%
2 3411
 
6.0%
3 1949
 
3.4%
4 1289
 
2.3%
5 896
 
1.6%
6 669
 
1.2%
7 524
 
0.9%
8 434
 
0.8%
9 338
 
0.6%
ValueCountFrequency (%)
73 1
 
< 0.1%
72 1
 
< 0.1%
71 2
< 0.1%
70 2
< 0.1%
69 2
< 0.1%
68 3
< 0.1%
67 3
< 0.1%
66 3
< 0.1%
65 4
< 0.1%
64 4
< 0.1%

artist_skip_rate_bins
Categorical

MISSING 

Distinct20
Distinct (%)< 0.1%
Missing1863
Missing (%)3.3%
Memory size499.3 KiB
65.0-70.0%
11309 
60.0-65.0%
9336 
70.0-75.0%
6656 
55.0-60.0%
4996 
95.0-100.0%
4993 
Other values (15)
17448 

Length

Max length11
Median length10
Mean length10.087891
Min length8

Characters and Unicode

Total characters552191
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45.0-50.0%
2nd row65.0-70.0%
3rd row70.0-75.0%
4th row75.0-80.0%
5th row80.0-85.0%

Common Values

ValueCountFrequency (%)
65.0-70.0% 11309
20.0%
60.0-65.0% 9336
16.5%
70.0-75.0% 6656
11.8%
55.0-60.0% 4996
8.8%
95.0-100.0% 4993
8.8%
45.0-50.0% 3297
 
5.8%
75.0-80.0% 3295
 
5.8%
50.0-55.0% 2513
 
4.4%
80.0-85.0% 1955
 
3.5%
85.0-90.0% 1756
 
3.1%
Other values (10) 4632
8.2%
(Missing) 1863
 
3.3%

Length

2024-05-15T13:44:55.840352image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
65.0-70.0 11309
20.7%
60.0-65.0 9336
17.1%
70.0-75.0 6656
12.2%
55.0-60.0 4996
9.1%
95.0-100.0 4993
9.1%
45.0-50.0 3297
 
6.0%
75.0-80.0 3295
 
6.0%
50.0-55.0 2513
 
4.6%
80.0-85.0 1955
 
3.6%
85.0-90.0 1756
 
3.2%
Other values (10) 4632
8.5%

Most occurring characters

ValueCountFrequency (%)
0 169207
30.6%
. 109476
19.8%
5 68057
12.3%
- 54738
 
9.9%
% 54738
 
9.9%
6 34977
 
6.3%
7 27916
 
5.1%
8 8961
 
1.6%
9 8865
 
1.6%
4 6047
 
1.1%
Other values (3) 9209
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 333239
60.3%
Other Punctuation 164214
29.7%
Dash Punctuation 54738
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 169207
50.8%
5 68057
20.4%
6 34977
 
10.5%
7 27916
 
8.4%
8 8961
 
2.7%
9 8865
 
2.7%
4 6047
 
1.8%
1 5506
 
1.7%
3 2828
 
0.8%
2 875
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 109476
66.7%
% 54738
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 54738
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 552191
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 169207
30.6%
. 109476
19.8%
5 68057
12.3%
- 54738
 
9.9%
% 54738
 
9.9%
6 34977
 
6.3%
7 27916
 
5.1%
8 8961
 
1.6%
9 8865
 
1.6%
4 6047
 
1.1%
Other values (3) 9209
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 552191
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 169207
30.6%
. 109476
19.8%
5 68057
12.3%
- 54738
 
9.9%
% 54738
 
9.9%
6 34977
 
6.3%
7 27916
 
5.1%
8 8961
 
1.6%
9 8865
 
1.6%
4 6047
 
1.1%
Other values (3) 9209
 
1.7%

Interactions

2024-05-15T13:44:30.000485image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:15.340088image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:17.862693image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:19.709421image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:21.621255image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:23.893475image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:26.159852image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:28.086533image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:30.237279image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:15.728654image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:18.130529image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:19.922418image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:21.874339image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:24.168929image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:26.360852image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:28.329623image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:30.467366image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:16.231989image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:18.377208image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:20.148765image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:22.128253image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:24.577489image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:26.590602image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:28.606534image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:30.661364image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:16.565885image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:18.589439image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:20.344720image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:22.350257image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:24.935649image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:26.767546image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:28.838596image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:30.874117image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:16.825880image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:18.803921image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:20.601892image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:22.612252image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:25.235262image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:26.966037image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:29.058525image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:31.108119image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:17.128232image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:19.048889image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:20.853892image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:22.858811image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:25.499702image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:27.171735image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:29.312390image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:31.327023image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:17.394567image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:19.262811image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:21.119443image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:23.107807image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:25.718629image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:27.563958image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:29.541219image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:31.539020image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:17.611665image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:19.474504image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:21.351255image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:23.555633image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:25.929856image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:27.834607image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T13:44:29.755442image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Missing values

2024-05-15T13:44:32.041109image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-15T13:44:33.134228image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-15T13:44:34.174197image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

tsusernameplatformms_playedconn_countryip_addr_decrypteduser_agent_decryptedmaster_metadata_track_namemaster_metadata_album_artist_namemaster_metadata_album_album_namespotify_track_uriepisode_nameepisode_show_namespotify_episode_urireason_startreason_endshuffleskippedofflineoffline_timestampincognito_modehourtime_of_dayplay_countskipped_last_timealbum_play_countartist_play_countartist_skip_rate_so_farprevious_skippedcurrent_listening_streakartist_skip_rate_bins
1359442022-10-14 20:19:47+00:007h7t32c2zzbfixxoo414zkhuliPhone90791PL31.60.48.10NoneIf You Were There, BewareArctic MonkeysFavourite Worst Nightmarespotify:track:0idZZsnM7nuSYanlpKTuwVNoneNoneNonetrackdoneunexpected-exit-while-paused00False1665778696False20noc0.000.00.00.00000000NaN
1359452022-10-15 09:34:25+00:007h7t32c2zzbfixxoo414zkhuliPhone161726PL31.60.48.10NoneWUJEK DOBRA RADATaco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:5jumw9HzKWgSruqVgfajukNoneNoneNoneclickrowtrackdone10False1665826304False9środek dnia0.000.00.00.00000001NaN
1359462022-10-15 09:34:44+00:007h7t32c2zzbfixxoo414zkhuliPhone17493PL31.60.48.10NoneWUJEK DOBRA RADATaco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:5jumw9HzKWgSruqVgfajukNoneNoneNonetrackdoneendplay11False1665826465False9środek dnia1.001.01.00.5000000245.0-50.0%
1359472022-10-15 09:38:16+00:007h7t32c2zzbfixxoo414zkhuliPhone204730PL31.60.48.10NoneWYTRAWNE (Z NUTĄ DESPERACJI)Taco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:2Mxs1xRmWFdxtpyRLiFsVMNoneNoneNoneclickrowfwdbtn11False1665826485False9środek dnia0.002.02.00.6666671065.0-70.0%
1359482022-10-15 09:38:17+00:007h7t32c2zzbfixxoo414zkhuliPhone750PL31.60.48.10NoneWYTRAWNE (Z NUTĄ DESPERACJI)Taco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:2Mxs1xRmWFdxtpyRLiFsVMNoneNoneNonefwdbtnfwdbtn11False1665826697False9środek dnia1.013.03.00.7500001070.0-75.0%
1359492022-10-15 09:38:22+00:007h7t32c2zzbfixxoo414zkhuliPhone4070PL31.60.48.10NoneWYTRAWNE (Z NUTĄ DESPERACJI)Taco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:2Mxs1xRmWFdxtpyRLiFsVMNoneNoneNonefwdbtnendplay11False1665826698False9środek dnia2.014.04.00.8000001075.0-80.0%
1359502022-10-15 09:38:26+00:007h7t32c2zzbfixxoo414zkhuliPhone4540PL31.60.48.10NoneWYTRAWNE (Z NUTĄ DESPERACJI)Taco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:2Mxs1xRmWFdxtpyRLiFsVMNoneNoneNoneclickrowendplay11False1665826702False9środek dnia3.015.05.00.8333331080.0-85.0%
1359512022-10-15 09:38:27+00:007h7t32c2zzbfixxoo414zkhuliPhone890PL31.60.48.10NoneWUJEK DOBRA RADATaco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:5jumw9HzKWgSruqVgfajukNoneNoneNoneclickrowendplay01False1665826706False9środek dnia2.016.06.00.8571431085.0-90.0%
1359522022-10-15 09:41:29+00:007h7t32c2zzbfixxoo414zkhuliPhone182710PL31.60.48.10NoneTIJUANATaco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:548azCoBz3imDTaxPBn0xCNoneNoneNoneclickrowendplay01False1665826707False9środek dnia0.007.07.00.8750001085.0-90.0%
1359532022-10-15 09:44:47+00:007h7t32c2zzbfixxoo414zkhuliPhone199186PL31.60.48.10NoneALERT RCBTaco HemingwayPOCZTÓWKA Z WWA, LATO '19spotify:track:1lrB0ToooiludrdlNlQ1QdNoneNoneNoneclickrowtrackdone00False1665826890False9środek dnia0.008.08.00.7777781075.0-80.0%
tsusernameplatformms_playedconn_countryip_addr_decrypteduser_agent_decryptedmaster_metadata_track_namemaster_metadata_album_artist_namemaster_metadata_album_album_namespotify_track_uriepisode_nameepisode_show_namespotify_episode_urireason_startreason_endshuffleskippedofflineoffline_timestampincognito_modehourtime_of_dayplay_countskipped_last_timealbum_play_countartist_play_countartist_skip_rate_so_farprevious_skippedcurrent_listening_streakartist_skip_rate_bins
1925352023-07-15 18:02:04+00:007h7t32c2zzbfixxoo414zkhuliPhone580PL31.60.79.67NaNTime to PretendMGMTOracular Spectacularspotify:track:4iG2gAwKXsOcijVaVXzRPWNoneNoneNonefwdbtnfwdbtn11False1689444123False18zachód słońca56.01205.0227.00.7500001070.0-75.0%
1925362023-07-15 18:02:05+00:007h7t32c2zzbfixxoo414zkhuliPhone590PL31.60.79.67NaNBeat ItMichael JacksonThriller 25 Super Deluxe Editionspotify:track:1OOtq8tRnDM8kG2gqUPjAjNoneNoneNonefwdbtnfwdbtn11False1689444125False18zachód słońca22.0153.0186.00.7914441075.0-80.0%
1925372023-07-15 18:02:05+00:007h7t32c2zzbfixxoo414zkhuliPhone610PL31.60.79.67NaNWish I Knew YouThe RevivalistsMen Amongst Mountainsspotify:track:2EWpa5XnAuSn0sIkSSIhYkNoneNoneNonefwdbtnfwdbtn11False1689444124False18zachód słońca3.013.03.00.7500001070.0-75.0%
1925382023-07-15 18:02:06+00:007h7t32c2zzbfixxoo414zkhuliPhone610PL31.60.79.67NaNMind MischiefTame ImpalaLonerismspotify:track:6ewQE1dNPv9qqlnB1CxrvMNoneNoneNonefwdbtnfwdbtn11False1689444125False18zachód słońca14.0140.0310.00.7749201075.0-80.0%
1925392023-07-15 18:02:07+00:007h7t32c2zzbfixxoo414zkhuliPhone560PL31.60.79.67NaNHow to Disappear CompletelyRadioheadKID A MNESIAspotify:track:7hFmiFUYmIjELj5d0UjbVhNoneNoneNonefwdbtnfwdbtn11False1689444127False18zachód słońca13.0118.01007.00.5634921055.0-60.0%
1925402023-07-15 18:02:07+00:007h7t32c2zzbfixxoo414zkhuliPhone740PL31.60.79.67NaNYou Are the Right OneSportsNaked All the Timespotify:track:2qpacEyFxmbxCpIEqZkqvCNoneNoneNonefwdbtnfwdbtn11False1689444126False18zachód słońca25.0125.027.00.7500001070.0-75.0%
1925412023-07-15 18:02:08+00:007h7t32c2zzbfixxoo414zkhuliPhone560PL31.60.79.67NaNBanquetBloc PartySilent Alarmspotify:track:4juzduULFJiZVIcrC1tkxENoneNoneNonefwdbtnfwdbtn11False1689444127False18zachód słońca43.0145.046.00.8936171085.0-90.0%
1925422023-07-15 18:02:08+00:007h7t32c2zzbfixxoo414zkhuliPhone440PL31.60.79.67NaNLet You DownDawid PodsiadłoLet You Downspotify:track:1qpGMJi0ippCaMUOs7cz2qNoneNoneNonefwdbtnfwdbtn11False1689444128False18zachód słońca26.0126.0727.00.7472531070.0-75.0%
1925432023-07-15 18:02:09+00:007h7t32c2zzbfixxoo414zkhuliPhone490PL31.60.79.67NaNSpace SongBeach HouseDepression Cherryspotify:track:1ZgMsA55GIY7ICkQh5MILANoneNoneNonefwdbtnfwdbtn11False1689444129False18zachód słońca48.0158.0153.00.8376621080.0-85.0%
1925442023-07-15 18:02:09+00:007h7t32c2zzbfixxoo414zkhuliPhone530PL31.60.79.67NaNMythBeach HouseBloomspotify:track:2Zw3HNjaNV42LnQ2uY5JQsNoneNoneNonefwdbtnfwdbtn11False1689444128False18zachód słońca30.0160.0154.00.8387101080.0-85.0%